Time Series Forecasting Using Deep Learning Example is wrong

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Hi
I´m new in use of Deep Learning toolbox.
I was try execute the example 'Time Series Forecasting Using Deep Learning'
but it has an error (Matrix dimensions must agree.) in line:
rmse = sqrt(mean((YPred-YTest).^2))
YPred and YTest don´t have the same dimensions, and then if i truncate rmse value, the code has other error (Vectors must be the same length.) in line:
plot(idx,[data(numTimeStepsTrain) YPred],'.-')
So, how i can solve this problem?
Thank you.
Regards.
  2 Comments
Mohammad Sami
Mohammad Sami on 30 Mar 2020
Did you accidently change something in the example. did you run from the beginning ? i dont get any error on mine
openExample('nnet/TimeSeriesForecastingUsingDeepLearningExample')
Andriy Chubatyy
Andriy Chubatyy on 30 Mar 2020
Yes, i changed one think and it is my mistake, in line:
[net,YPred] = predictAndUpdateState(net,YTrain(end)); --> [net,YPred] = predictAndUpdateState(net,YTrain);
because i had error:
The construct "YTrain(...end...)" is ambiguous in this context, because "YTrain" cannot be ascertained to be either the name of a variable or of a function. To make it a variable, assign to it; to allow it to become a function at execution time, replace "end" with a call to LENGTH, SIZE, or NUMEL on the desired array.
So this line: [net,YPred] = predictAndUpdateState(net,YTrain(end)); if i execute it in script editor it give me a error but if i execute it in command window is good.
And yes, i run from the beginning.
Now i executed:
openExample('nnet/TimeSeriesForecastingUsingDeepLearningExample')
step by step and it is working.
thank you Mohammad, regards.

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